From Novice to Becoming Expert?
One can learn to play chess in a few hours. One can also master a few standard opening games and become good at playing chess. What next? I wonder what would take one from that point to becoming a grandmaster. Is being a chess prodigy a matter of good genes or a result of lots of practice? The answer to that has a bearing on the age-old question of how one becomes an expert. This topic has fascinated generations of pandits who have written numerous press articles and books on the subject.
Reading these books and articles, one finds that theories promoted have very little scientific support. Those theories seem to reflect the biases or the morality of the authors — such as hard work is necessary. For instance, Malcolm Gladwell [1* below], who is an author of trendy books, wrote that one would take 10,000 hours or ten years of conscious practice in a domain to become an expert. Critical thinking can easily punch holes in that proposition. How would the author explain that not all chess grandmasters have had to work that hard or for that long before becoming one? Does it seem reasonable to believe that any novice player practicing for 10,000 hours plus would become a grandmaster?
This debate about good genes, culture, and innate ability versus practice make perfect viewpoints is not entirely helpful to have. To me, this is hardly an academic debate. Instead, to shed some light on this, let’s look at research from cognitive science, which is a study of brain processes. Specifically, I shall look at what they say about how experts differ from novices in learning new facts. Understanding this could lead us to devise effective teaching methods for even average students.
Key results from recent research in cognitive science that are relevant to this topic are
1) learning new facts occurs in the context of pre-existing knowledge, i.e., it is an extension and modification of what is known before.
2) Humans store facts in two types of memory — short-term and long-term memories.
3) Our short-term memory (STM) has limited capacity. New facts continually replace earlier ones learned; thus, the ability to recall those facts lapses with time unless we transfer these to our long-term memory (LTM).
4) Recall (and reuse) of facts long-ago learned takes place from long-term memory. Thus, the transfer from short-term memory to long-term memory is essential for learning.
5) This transfer is unlike the familiar example of copying data from computer memory to disk storage.
There is not a one-to-one correspondence between what is stored in each memory. Short-term memories are about remembering facts as presented, whereas Long-term memory stores facts within conceptual frameworks. That means new facts are integrated with other previously stored information. That transfer process is known as learning facts instead of simply knowing the facts. This transfer consists of an understanding of facts and ideas in the context of a conceptual framework formulated and enriched continually as new facts are added to current knowledge. This transfer is very advantageous because storing facts thus allows one to store a larger volume of facts and helps in efficient recall.
Expert applies learned knowledge to situations where a novice will struggle to think of doing. Researchers have shown that experts differ from novices because they build a richer conceptual framework. An expert can store larger amounts of facts, fast recall, and connect dots to apply to similar situations compared to a beginner. In short, an expert can see patterns and similarities which are not visible to novices. Moreover, an expert learns new related facts more quickly, and their learning process continually enriches the conceptual framework used to store facts.
Chase & Simon [1981, 2* below] estimated that expert chess players have a vocabulary of 50,000 patterns representing familiar configurations of chess pieces. Several researchers have made a similar observation for fields such as games of Bridge and Go, medical diagnosis, physical sciences, and computer programming. In all of these, it was shown that experts could store many domain-specific patterns and have instant recall.
A particularly striking example of recall ability is the experiment conducted by Ericsson and Chase [3* below]. They experimented to test a person’s ability to recall a random string of digits. An adult subject was asked to recall strings of digits repeated one per second. In the beginning, he was able to recall on average seven digits, which is typical for an adult. After about 250 hours of practice, though, he could recall 80 digits randomly generated. It turns out that that person was an avid runner and his recall improved as he started to associate numbers presented in bunches and relate those bunches to his running times of previous races.
This is a clear example where a person forms a conceptual framework that allows fast recall and develops the ability to store many unrelated facts. It is speculated that experts’ ability to recall and store many facts or patterns is due to a similar process of digesting facts.
Two things are notable: the conceptual framework and resulting skilled memory are very domain-specific, and it is hard to explicitly describe this framework’s principle. The details of a framework remain subjective and hidden, rarely explained or explainable to others. An expert’s information retrieval will seem like a mysterious process to others. Moreover, as the complexity of information increases, an expert can also transfer that knowledge to a different domain whenever a similar pattern is observed.
But some people may be able to construct a rich conceptual framework for a domain with fewer repetitions.
The classroom teacher-centric model simply enables students to store facts into their short-term memories. Real learning will only occur when students organize absorb facts into a framework while transferring these facts to LTM. Using active learning teaching methods is believed to be better at the transfer process from STM to LTM. Additionally,
If a teacher explains the importance of building rich conceptual structures in the context of a domain under study, the students are more likely to learn faster and more effectively.
Below are links to some interesting articles on the subject:
1*: https://en.wikipedia.org/wiki/Outliers_(book)
3*: https://link.springer.com/content/pdf/10.3758/BF03330462.pdf